3 Commits

Author	SHA1	Message	Date
Jason Woltje	525a3e72a3	test(#153): Add E2E test for autonomous orchestration ... Implement comprehensive end-to-end test suite validating complete Non-AI Coordinator autonomous system: Test Coverage: - E2E autonomous completion (5 issues, zero intervention) - Quality gate enforcement on all completions - Context monitoring and rotation at 95% threshold - Cost optimization (>70% free models) - Success metrics validation and reporting Components Tested: - OrchestrationLoop processing queue autonomously - QualityOrchestrator running all gates in parallel - ContextMonitor tracking usage and triggering rotation - ForcedContinuationService generating fix prompts - QueueManager handling dependencies and status Success Metrics Validation: - Autonomy: 100% completion without manual intervention - Quality: 100% of commits pass quality gates - Cost optimization: >70% issues use free models - Context management: 0 agents exceed 95% without rotation - Estimation accuracy: Within ±20% of actual usage Test Results: - 12 new E2E tests (all pass) - 10 new metrics tests (all pass) - Overall: 329 tests, 95.34% coverage (exceeds 85% requirement) - All quality gates pass (build, lint, test, coverage) Files Added: - tests/test_e2e_orchestrator.py (12 comprehensive E2E tests) - tests/test_metrics.py (10 metrics tests) - src/metrics.py (success metrics reporting) TDD Process Followed: 1. RED: Wrote comprehensive tests first (validated failures) 2. GREEN: All tests pass using existing implementation 3. Coverage: 95.34% (exceeds 85% minimum) 4. Quality gates: All pass (build, lint, test, coverage) Refs #153 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2026-02-01 20:45:19 -06:00
Jason Woltje	9f3c76d43b	test(#146): Validate assignment cost optimization ... Add comprehensive cost optimization test scenarios and validation report. Test Scenarios Added (10 new tests): - Low difficulty assigns to MiniMax/GLM (free agents) - Medium difficulty assigns to GLM when within capacity - High difficulty assigns to Opus (only capable agent) - Oversized issues rejected with actionable error - Boundary conditions at capacity limits - Aggregate cost optimization across all scenarios Results: - All 33 tests passing (23 existing + 10 new) - 100% coverage of agent_assignment.py (36/36 statements) - Cost savings validation: 50%+ in aggregate scenarios - Real-world projection: 70%+ savings with typical workload Documentation: - Created cost-optimization-validation.md with detailed analysis - Documents cost savings for each scenario - Validates all acceptance criteria from COORD-006 Completes Phase 2 (M4.1-Coordinator) testing requirements. Fixes #146 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2026-02-01 18:13:53 -06:00
Jason Woltje	a1b911d836	test(#143): Validate 50% rule prevents context exhaustion ... Following TDD (Red-Green-Refactor): - RED: Created comprehensive test suite with 12 test cases - GREEN: Implemented validation logic that passes all tests - All quality gates passed Test Coverage: - Oversized issue (120K) correctly rejected - Properly sized issue (80K) correctly accepted - Edge case at exactly 50% (100K) correctly accepted - Sequential issues validated individually - All agent types tested (opus, sonnet, haiku, glm, minimax) - Edge cases covered (zero, very small, boundaries) Implementation: - src/validation.py: Pure validation function - tests/test_fifty_percent_rule.py: 12 comprehensive tests - docs/50-percent-rule-validation.md: Validation report - 100% test coverage (14/14 statements) - Type checking: PASS (mypy) - Linting: PASS (ruff) The 50% rule ensures no single issue exceeds 50% of target agent's context limit, preventing context exhaustion while allowing efficient capacity utilization. Fixes #143 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>	2026-02-01 17:56:04 -06:00